AI Enablement Architect Lead

Role Overview

The AI Enablement Architect Lead will be an innovator of AI solutions, understanding the future of AI technologies and how they can provide transformation and efficiency opportunities for the EA Experiences organization. They will report to and collaborate closely with the Head of AI Enablement for EA Experiences and collaborate closely with a global team across Europe, North America, and Southeast Asia.

What You Will Do

The role will define requirements, rapidly prototype, iterate with stakeholders, and establish reusable architectures, standards, and patterns using the latest AI engineering methodologies, models, tools, and platforms. You will be hands-on creating and implementing scalable solutions and workflows that enable teams to spend more time on high-value, creative, and strategic work and drive significant revenue for EA.

Why It Might Be a Fit

You will be a hybrid worker, collaborating with teams 3 days a week from the Galway office; international travel to collaborate with global teams is an added bonus. You will be creative, innovative, self-motivated, and team-first, equally strong at problem-solving and collaborating across creative, product, marketing, data, and engineering teams.

Requirements

• 8+ years of experience architecting, prototyping, and deploying robust production solutions that incorporate software engineering, infrastructure, architectural, and security best practices
• Strong Python development skills; experience with C#, JavaScript, HTML, and CSS is beneficial
• Hands-on experience using agentic AI software engineering solutions (e.g., Claude Code, Kiro, or similar) to accelerate development and experimentation
• 3+ years implementing AI solutions driving measurable business impact
• Excellent working knowledge of: prompt and context engineering; AI agents, agentic architectures, tool calling, and Model Context Protocol (MCP); AI assistants, RAG, embeddings, and vector databases, evaluation, benchmarking, and guardrails
• Experience tuning language and diffusion models, labeling and tagging data, and architecting data pipelines
• Deep understanding of architecture and design principles, and cloud services, specifically AWS, Azure and GCP are beneficial
• Enterprise architecture and micro-services design; observability and telemetry; infrastructure as code and CI/CD pipelines

Benefits

• healthcare coverage
• mental well-being support
• retirement savings
• paid time off
• family leaves
• complimentary games